Deep Learning
This page contains resources about Deep Learning and Representation Learning . Subfields * Deep Generative Models ** Deep Directed Networks ** Deep Boltzmann Machine ** Deep Belief Network * Deep Neural Networks ** Deep Multi-Layer Perceptrons ** Deep Autoencoders ** Stacked denoising Autoencoders Online Courses Video Lectures *Neural Networks for Machine Learning by Geoffrey Hinton - Coursera *Neural networks class by Hugo Larochelle (Youtube ) *Deep Learning and Neural Networks by Kevin Duh *Computer Perception with Deep Learning by Yann LeCun (Part 1 , Part 2 ) *Computational Neuroscience and Learning by Eugenio Culurciello (Youtube) *A tutorial on Deep Learning by Geoffrey Hinton - VideoLectures.Net Lecture Notes *Deep Learning by Yann LeCun *Unsupervised Feature Learning and Deep Learning (UFLDL) by Andrew Ng *Deep Learning by Bhiksha Raj *Representation Learning by Yoshua Bengio *Convolutional Neural Networks for Visual Recognition by Fei-Fei Li & Andrej Karpathy *Deep Learning by Sargur Srihari Books and Book Chapters * Bengio, Y. (2009). Learning Deep Architectures for AI. Foundations and Trends® in Machine Learning, 2(1), 1-127. Now Publishers. * Orr, G. B., & Müller, K. R. (2012). Neural Networks: Tricks of the Trade. Springer. *Murphy, K. P. (2012). "Chapter 28: Deep Learning". Machine Learning: A Probabilistic Perspective. MIT Press. * Bengio, Y., & Courville, A. (2013). Deep Learning of Representations. Springer. * Deng, L., & Yu, D. (2014). Deep Learning: Methods and Applications. Microsoft Research. * Theodoridis, S. (2015). "Chapter 18: Neural Networks and Deep Learning". Machine Learning: A Bayesian and Optimization Perspective. Academic Press. * Gibson, A., & Patterson J. (2016). Deep Learning: A Practitioner's Approach. * Bengio, Y., Goodfellow, I. J., & Courville, A. (TBA). Deep Learning. MIT Press. (draft) Scholarly Articles See Reading List and Recommended Readings for the complete list. Tutorials *UFLDL Tutorial *A Deep Learning Tutorial: From Perceptrons to Deep Networks - with Java examples *Neural Networks, Manifolds, and Topology - advanced *Learning Invariant Feature Hierarchies (2013) and its Panel Discussion *Deep Learning Tutorial (ICML 2013) *Deep Learning for Computer Vision (NIPS 2013) *Deep Learning for NLP (NAACL 2013) *Deep Support Vector Machines (ROKS 2013) *Deep Learning of Representaions (SSTiC 2013) *Deep Learning for Machine Vision (BMVC 2013) *Deep Learning for Computer Vision (NIPS 2013) (Video ) *Deep Learning Methods for Vision (CVPR 2012) *Deep Learning for NLP (ACL 2012) *Representation Learning (ICML 2012) *Classification with Deep Invariant Scattering Networks (NIPS 2012) *A tutorial on deep and unsupervised feature learning for activity recognition (2011) *Tutorial on Deep Learning and Applications (NIPS 2010) *A tutorial on Deep Learning (2009) *Tutorial on Learning Deep Architectures (ICML 2009) *Learning Deep Hierarchies of Representations (2009) *Deep Learning with Multiplicative Interactions (NIPS 2009) *Learning Feature Hierarchies (MLSS 2009) *Deep Belief Networks (MLSS 2009) Software See Software Links for the complete list. *TensorFlow - open source *deeplearning4j - Java *CudaCnn - MATLAB *hebel - Python *ConvNetJS - Deep Learning models (mainly Neural Networks) entirely in your browser *Caffe - Deep Learning framework *visual-rbm *Learning Deep Boltzmann Machines - MATLAB *Estimating Partition Functions of RBM's - MATLAB *Deep Belief Networks - MATLAB See also *Deep Learning in the news (blog) Other Resources * Deep Learning Reading List * DeepLearning.Net * Toronto Deep Learning Demos - source code *Deep learning from the bottom up - Metacademy *Neural Networks and Deep Learning - free online book *Deep Learning (Building Intelligent Probabilistic Systems) - Blog by Harvard University *Benchmark of Deep Learning Representations for Visual Recognition *Deep Learning Playlist - Youtube collection of video lectures and tutorials *Deep Learning on Google+ - online community *A Short History of and Introduction to Deep Learning - Presentation by John Kaufhold *An Introduction to Deep Learning: From Perceptrons to Deep Networks - tutorial with Java examples *Graduate Summer School: Deep Learning, Feature Learning by IPAM, UCLA *What Does a Neural Network Actually Do? - Neural Networks and Deep Learning *Ersatz - Deep Neural Networks in the cloud *Bibliography in Deep Learning - collection of papers categorized according to type of application Category:Machine Learning Category:Computational Neuroscience